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oiwe's Introduction

#Interpretable Word Embeddings

##Overview This tool provide a method of interpretable word embeddings, which is based on OIWE-IPG model in our paper, Online Learning of Interpretable Word Embeddings.

##Usage

####In Directory word2nve-c/: Use command "make" to compile sourse files in directory. OIWE model is realized in word2nvec.c

####In Directory bin/: The command to run OIWE model is in launcher.sh. Configurations in launcher.sh can be modified. Use "sh launcher.sh" to run the model.

format: ./word2vec -train -output -size -threads -binary <save as binary: 0 or 1> -cbow 0

##Experiments

####Data

####Word Similarty Task

Task name Word pairs Pairs found OIWE-IPG OIWE-NPG Skip-gram RNN
WS-353 353 351 0.6415 0.5833 0.6380 0.3675
WS-353-SIM 203 202 0.7174 0.6371 0.6735 0.4928
WS-353-REL 252 251 0.6032 0.5788 0.6039 0.2925
MC-30 30 30 0.6245 0.5245 0.5041 0.5826
RG-65 65 65 0.5716 0.5685 0.5049 0.5019
Rare-Word 2034 951 0.3379 0.2544 0.3694 0.3904
MEN 3000 2987 0.5760 0.5668 0.5256 0.4344
MTurk-287 287 284 0.6054 0.5350 0.5848 0.5093
MTurk-771 771 769 0.4981 0.4147 0.4965 0.3990
YP-130 139 118 0.3066 0.1808 0.2493 0.4021

####Spearman Coefficient - dimension

Dimension Number OIWE Skip-gram
100 62.851 64.724
200 66.45 64.387
300 71.74 67.35
400 66.74 64.82
500 64.118 66.046

####Word Intrusion

Model Precision(%)
Skip-gram 32.62
NNSE 92.00
OIWE-NPG 61.40
OIWE-IPG 94.80

oiwe's People

Contributors

luohongyin avatar

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